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首页> 外文期刊>Magnetic resonance imaging: An International journal of basic research and clinical applications >Accuracy of gamma-variate fits to concentration-time curves from dynamic susceptibility-contrast enhanced MRI: Influence of time resolution, maximal signal drop and signal-to-noise
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Accuracy of gamma-variate fits to concentration-time curves from dynamic susceptibility-contrast enhanced MRI: Influence of time resolution, maximal signal drop and signal-to-noise

机译：γ变量的准确性与动态磁化率对比增强MRI的浓度-时间曲线拟合：时间分辨率，最大信号降和信噪比的影响

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Concentration-time curves derived from dynamic susceptibility-contrast enhanced magnetic resonance imaging are widely used to calculate cerebrovascular parameters, To exclude effects of recirculation, a nonlinear regression method is used to fit a Gamma-variate function to the concentration-time course, In previous studies the errors arising from the fitting procedure have not been quantified. In a computer simulation we investigate the uncertainties of parameters calculated from the fitted Gamma-variate function, exploring the dependencies on signal-to-noise (SNR), time resolution (Delta t), and maximal signal drop (MSD), Our study was performed to give a framework on how to design MR-sequences and choose contrast media and their application in order to yield concentration-time curves which allow a reliable performance of the Gamma-variate fitting procedure, We recorded 396 concentration-time curves from regions of interest of 40 patients, The Gamma-variate fitting procedure was applied to these curves resulting in 396 parameter sets, Ideal concentration-time curves as Gamma-variate functions were generated from these sets with a given Gamma t, MSD, and SNR, Recirculation effect was simulated, Then the Gamma-variate fitting was performed again, From ideal and simulated Gamma-variate function the area and the normalized first moment were calculated, The uncertainties of the values calculated from the simulated curve relating to the values of the original one were determined, Increase of SNR decreases the involved errors, With SNR values of 100 and more there is only minor influence of Delta t and MSD and the fitted curve approximates the original data very well, Smaller values of SNR lead to a stronger influence of Delta t and MSD and a higher number of fitting failures, With increasing Delta t the uncertainties also increase, Intermediate values of MSD (30% to 70%) yield the smallest errors while increasing or decreasing MSD yields an increase of uncertainty, To achieve low uncertainties in the calculation of cerebrovascular parameters from Gamma-variate fits, Delta t of the imaging sequence and MSD must be considered, This is more important the lower SNR is, The shown dependencies should be taken into account when choosing MR sequence parameters and application of contrast media. (C) 1997 Elsevier Science Inc.
机译：从动态磁化率对比增强磁共振成像得出的浓度-时间曲线被广泛用于计算脑血管参数，为了排除再循环的影响，使用非线性回归方法将伽玛变量函数拟合到浓度-时间过程中。研究由于拟合过程而引起的误差尚未量化。在计算机仿真中，我们调查了根据拟合的伽马变量函数计算出的参数的不确定性，并探索了对信噪比（SNR），时间分辨率（Delta t）和最大信号降（MSD）的依赖性。进行了研究，以提供有关如何设计MR序列和选择造影剂及其应用的框架，以生成允许可靠地执行Gamma变量拟合过程的浓度-时间曲线的方法，我们记录了396个区域的浓度-时间曲线感兴趣的40位患者，将Gamma变量拟合程序应用于这些曲线，得到396个参数集，在给定的Gamma t，MSD和SNR的情况下，从这些集合生成了理想的浓度-时间曲线，作为Gamma变量函数进行模拟，然后再次进行Gamma变量拟合，从理想和模拟的Gamma变量函数计算出面积和归一化的第一矩，确定了从模拟曲线计算出的与原始曲线值有关的值，SNR的增加减小了所涉及的误差，SNR值为100或更大时，Delta t和MSD的影响较小，拟合曲线近似原始数据很好的是，较小的SNR值会导致Delta t和MSD的影响更大，并且装配失败次数也会增加。随着Delta t的增加，不确定性也会增加，MSD的中间值（30％至70％）产生的误差最小，而增大或减小MSD会导致不确定性增加，要在通过伽玛变量拟合计算脑血管参数时实现较低的不确定性，必须考虑成像序列和MSD的Delta t，这对于降低SNR更为重要，显示的依赖性选择MR序列参数和使用造影剂时应考虑到这一点。 （C）1997爱思唯尔科学公司

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